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放化疗期间及之后的肿瘤体积缩小:宏观描述

Tumor Volume Regression during and after Radiochemotherapy: A Macroscopic Description.

作者信息

Castorina Paolo, Ferini Gianluca, Martorana Emanuele, Forte Stefano

机构信息

INFN, Sezione di Catania, 95123 Catania, Italy.

Faculty of Mathematics and Physics, Charles University, V Holešovičkách 2, 18000 Prague, Czech Republic.

出版信息

J Pers Med. 2022 Mar 26;12(4):530. doi: 10.3390/jpm12040530.

Abstract

Tumor volume regression during and after chemo and radio therapy is a useful information for clinical decisions. Indeed, a quantitative, patient oriented, description of the response to treatment can guide towards the modification of the scheduled doses or the evaluation of the best time for surgery. We propose a macroscopic algorithm which permits to follow quantitatively the time evolution of the tumor volume during and after radiochemotherapy. The method, initially validated with different cell-lines implanted in mice, is then successfully applied to the available data for partially responding and complete recovery patients.

摘要

化疗和放疗期间及之后肿瘤体积的缩小是临床决策的有用信息。实际上,对治疗反应进行定量的、以患者为导向的描述可以指导调整预定剂量或评估最佳手术时间。我们提出了一种宏观算法,该算法能够定量跟踪放化疗期间及之后肿瘤体积的时间演变。该方法最初在植入小鼠体内的不同细胞系上得到验证,随后成功应用于部分缓解和完全康复患者的现有数据。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3913/9025192/2886d8514b61/jpm-12-00530-g001.jpg

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